class_docstr: This `Field` represents a list of string tokens.  Before constructing this object, you need
  to tokenize raw strings using a :class:`~allennlp.data.tokenizers.tokenizer.Tokenizer`.
  
  Because string tokens can be represented as indexed arrays in a number of ways, we also take a
  dictionary of :class:`~allennlp.data.token_indexers.token_indexer.TokenIndexer`
  objects that will be used to convert the tokens into indices.
  Each `TokenIndexer` could represent each token as a single ID, or a list of character IDs, or
  something else.
  
  This field will get converted into a dictionary of arrays, one for each `TokenIndexer`.  A
  `SingleIdTokenIndexer` produces an array of shape (num_tokens,), while a
  `TokenCharactersIndexer` produces an array of shape (num_tokens, num_characters).
code: def as_tensor(
      self, padding_lengths: Dict[str, int]
  ) -> TextFieldTensors:
      if self._indexed_tokens is None:
          raise ConfigurationError(
              "You must call .index(vocabulary) on a field before calling .as_tensor()"
          )
  
      tensors = {}
  
      indexer_lengths: Dict[str, Dict[str, int]] = defaultdict(dict)
      for key, value in padding_lengths.items():
          # We want this to crash if the split fails. Should never happen, so I'm not
          # putting in a check, but if you fail on this line, open a github issue.
          indexer_name, padding_key = key.split("___")
          indexer_lengths[indexer_name][padding_key] = value
  
      for indexer_name, indexer in self.token_indexers.items():
          tensors[indexer_name] = indexer.as_padded_tensor_dict(
              self._indexed_tokens[indexer_name],
              indexer_lengths[indexer_name],
          )
      return tensors
  
imports: from collections import defaultdict
  from copy import deepcopy
  from typing import Dict, List, Optional, Iterator
  import textwrap
  from spacy.tokens import Token
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.data.fields.sequence_field import SequenceField
  from allennlp.data.tokenizers import Token
  from allennlp.data.token_indexers.token_indexer import TokenIndexer, IndexedTokenList
  from allennlp.data.vocabulary import Vocabulary
  from allennlp.nn import util
label_desc: Use image node_id 8 for calling the TextField obj's underlying member method code with example usage: obj.as_tensor(padding_lengths) and returns: tensors